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  • Title: Predicting physical interactions between protein complexes.
    Author: Clancy T, Rødland EA, Nygard S, Hovig E.
    Journal: Mol Cell Proteomics; 2013 Jun; 12(6):1723-34. PubMed ID: 23438732.
    Abstract:
    Protein complexes enact most biochemical functions in the cell. Dynamic interactions between protein complexes are frequent in many cellular processes. As they are often of a transient nature, they may be difficult to detect using current genome-wide screens. Here, we describe a method to computationally predict physical interactions between protein complexes, applied to both humans and yeast. We integrated manually curated protein complexes and physical protein interaction networks, and we designed a statistical method to identify pairs of protein complexes where the number of protein interactions between a complex pair is due to an actual physical interaction between the complexes. An evaluation against manually curated physical complex-complex interactions in yeast revealed that 50% of these interactions could be predicted in this manner. A community network analysis of the highest scoring pairs revealed a biologically sensible organization of physical complex-complex interactions in the cell. Such analyses of proteomes may serve as a guide to the discovery of novel functional cellular relationships.
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